Assessment of flood damages and benefits of remedial actions: "What are the weak links?"; with application to the Loire

Abstract

Flood damage models are used to determine the impact of measures to reduce damage due to river flooding. Such models are characterized by uncertainty. This uncertainty may affect the decisions made on the basis of the model outcomes. To reduce uncertainty effectively, the most important sources of uncertainty must be found. Uncertainty analysis serves this purpose.
By way of a questionnaire experts were asked about their judgment of the significance of uncertainty sources in flood damage assessment. The results of this questionnaire are compared to an uncertainty analysis by Monte Carlo Simulation, which Torterotot (1993) applied to the French model CIFLUPEDE.
The paper concludes that the role of uncertainty in flood damage assessment is highly significant and cannot be neglected. Both the experts and the analysis on the flood damage assessment model indicate the hydrologic relations ‘frequence of occurrence — river discharge — river water level’ and the damage estimates as the most important uncertainty sources. For embanked rivers dike breach is the most significant uncertainty source.
A question which appears is, taking into account these uncertainties, to what level of precision can flood damage assessment models predict the expected annual flood damage and the costs and revenues of flood alleviation measures? It is of importance to explore the boundaries of flood damage modeling and to try to find ways to move these boundaries. The uncertainty analysis presented in this paper can be seen as one more step on the way to this goal.

title = "Assessment of flood damages and benefits of remedial actions: {"}What are the weak links?{"}; with application to the Loire",

abstract = "Flood damage models are used to determine the impact of measures to reduce damage due to river flooding. Such models are characterized by uncertainty. This uncertainty may affect the decisions made on the basis of the model outcomes. To reduce uncertainty effectively, the most important sources of uncertainty must be found. Uncertainty analysis serves this purpose. By way of a questionnaire experts were asked about their judgment of the significance of uncertainty sources in flood damage assessment. The results of this questionnaire are compared to an uncertainty analysis by Monte Carlo Simulation, which Torterotot (1993) applied to the French model CIFLUPEDE. The paper concludes that the role of uncertainty in flood damage assessment is highly significant and cannot be neglected. Both the experts and the analysis on the flood damage assessment model indicate the hydrologic relations ‘frequence of occurrence — river discharge — river water level’ and the damage estimates as the most important uncertainty sources. For embanked rivers dike breach is the most significant uncertainty source. A question which appears is, taking into account these uncertainties, to what level of precision can flood damage assessment models predict the expected annual flood damage and the costs and revenues of flood alleviation measures? It is of importance to explore the boundaries of flood damage modeling and to try to find ways to move these boundaries. The uncertainty analysis presented in this paper can be seen as one more step on the way to this goal.",

T1 - Assessment of flood damages and benefits of remedial actions: "What are the weak links?"; with application to the Loire

AU - de Blois, Chris

AU - Wind, H.G.

PY - 1996

Y1 - 1996

N2 - Flood damage models are used to determine the impact of measures to reduce damage due to river flooding. Such models are characterized by uncertainty. This uncertainty may affect the decisions made on the basis of the model outcomes. To reduce uncertainty effectively, the most important sources of uncertainty must be found. Uncertainty analysis serves this purpose.
By way of a questionnaire experts were asked about their judgment of the significance of uncertainty sources in flood damage assessment. The results of this questionnaire are compared to an uncertainty analysis by Monte Carlo Simulation, which Torterotot (1993) applied to the French model CIFLUPEDE.
The paper concludes that the role of uncertainty in flood damage assessment is highly significant and cannot be neglected. Both the experts and the analysis on the flood damage assessment model indicate the hydrologic relations ‘frequence of occurrence — river discharge — river water level’ and the damage estimates as the most important uncertainty sources. For embanked rivers dike breach is the most significant uncertainty source.
A question which appears is, taking into account these uncertainties, to what level of precision can flood damage assessment models predict the expected annual flood damage and the costs and revenues of flood alleviation measures? It is of importance to explore the boundaries of flood damage modeling and to try to find ways to move these boundaries. The uncertainty analysis presented in this paper can be seen as one more step on the way to this goal.

AB - Flood damage models are used to determine the impact of measures to reduce damage due to river flooding. Such models are characterized by uncertainty. This uncertainty may affect the decisions made on the basis of the model outcomes. To reduce uncertainty effectively, the most important sources of uncertainty must be found. Uncertainty analysis serves this purpose.
By way of a questionnaire experts were asked about their judgment of the significance of uncertainty sources in flood damage assessment. The results of this questionnaire are compared to an uncertainty analysis by Monte Carlo Simulation, which Torterotot (1993) applied to the French model CIFLUPEDE.
The paper concludes that the role of uncertainty in flood damage assessment is highly significant and cannot be neglected. Both the experts and the analysis on the flood damage assessment model indicate the hydrologic relations ‘frequence of occurrence — river discharge — river water level’ and the damage estimates as the most important uncertainty sources. For embanked rivers dike breach is the most significant uncertainty source.
A question which appears is, taking into account these uncertainties, to what level of precision can flood damage assessment models predict the expected annual flood damage and the costs and revenues of flood alleviation measures? It is of importance to explore the boundaries of flood damage modeling and to try to find ways to move these boundaries. The uncertainty analysis presented in this paper can be seen as one more step on the way to this goal.